SYNCLAYER
AI-powered Design-to-Code Consistency Platform. A pre-MVP concept designed and built end-to-end to solve design drift between Figma and production code — with complete UX strategy, growth model, competitive analysis, user flows, and a fully functional interactive demo.
Next.js · TypeScript · Vercel · Figma
All metrics in this project are hypothetical, modeled from publicly available benchmarks of comparable dev tools (Chromatic, v0, Tokens Studio, Linear, Raycast). No real users were acquired. This project demonstrates growth strategy, measurement frameworks, and analytical reasoning.
The Problem
Design drift — the progressive divergence between design system specifications in Figma and their production implementations — compounds over time, increasing maintenance cost, degrading visual consistency, and creating friction between design and engineering teams.
Most teams rely on visual QA during pull requests (slow, subjective), periodic design audits (infrequent, deprioritized), or tribal knowledge (unscalable). None produce structured data or scale.
Drift Patterns
Color updated in Figma (#1A73E8 → #1B6FE0) but hardcoded hex values persist across 14 components
8px grid in Figma implemented inconsistently with mixed px, rem, and Tailwind classes
Card component padding/border-radius/shadow hierarchy diverges after 3 feature sprints
Font weights, line heights, letter-spacing accumulate small discrepancies
Business Cost
3–6h
Per team of 6 engineers
$13K–$26K
At $85/hr blended cost
The Solution
SyncLayer connects to a team's Figma workspace and GitHub repository, performs static analysis on both sides, and uses AI to surface mismatches with confidence-scored recommendations.
Reads both Figma and codebase, compares structurally — not just token export.
Every finding has a confidence %, reducing noise and false-positive fatigue.
Results delivered via PR comments, CI checks, Slack — not locked in a dashboard.
Findings explained with specific Figma node + code location references.
Drift velocity measured over time. No competitor offers this.
Competitive Landscape
Chromatic, Percy, Applitools
Compares code vs prior code, not code vs Figma. No design intent awareness.
Style Dictionary, Tokens Studio
Unidirectional (Figma → code). No audit. No component-level comparison.
Locofy, Anima, Figma Dev Mode
Read-only inspection or generation. No bidirectional audit or confidence scoring.
Copilot, Cursor, v0
Generation-focused, not audit-focused. No feedback loop against existing implementations.
ESLint, Stylelint
Cannot reason about design intent. No Figma awareness.
No existing tool performs bidirectional static analysis across Figma design files and production codebases to surface inconsistencies with confidence scoring and temporal tracking.
Target Personas
4–7 years
4+ hours/week manually verifying implementations match designs.
Adopts tools independently. Needs lead buy-in for team-wide.
7–12 years
Cannot measure design system adoption quantitatively. Reports to leadership are qualitative.
Owns DS roadmap. Can justify tooling spend to VP Design.
2–5 years
Gets PR comments about pixel inconsistencies. No systematic pre-commit check.
None on tooling. Adopts what the team adopts.
Information Architecture
SyncLayer
├── Dashboard (project overview)
├── Projects
│ ├── Settings
│ │ ├── Figma Connection
│ │ ├── GitHub Connection
│ │ ├── Scan Configuration
│ │ └── Notification Preferences
│ ├── Scans (history, filterable)
│ │ └── Scan Detail
│ │ ├── Summary (severity breakdown)
│ │ ├── Findings List (≥75% confidence)
│ │ │ └── Finding Detail
│ │ │ ├── Figma Reference
│ │ │ ├── Code Reference
│ │ │ ├── AI Explanation
│ │ │ ├── Confidence Score
│ │ │ ├── Golden Source Decision
│ │ │ └── Suggested Fix
│ │ └── Export (PDF, JSON, CSV)
│ └── Design Tokens
│ ├── Token Map (Figma ↔ Code)
│ ├── Coverage Report
│ └── Unmapped Tokens
├── Team Management
├── AI Insights
│ ├── Common Drift Patterns
│ ├── Drift Velocity
│ └── Component Health Scores
└── Settings
├── Account / Billing
├── Integrations
└── Trust & SafetyAI Finding Example
The Badge component (src/components/Badge.tsx, line 23) applies bg-blue-600 (resolved: #2563EB). The corresponding Figma component ("Badge / Default" in Design System v2.4) specifies fill color #1D4ED8.
Delta: 14 units in RGB space. Visually distinguishable at most screen sizes.
Suggested fix: Replace bg-blue-600 with bg-blue-700 or update the Figma source to match.
Design Principles
Every recommendation cites specific artifacts on both sides.
PR comments, CI checks, Slack. The dashboard is for deep dives.
Never the reason a deploy is delayed. Advisory mode first.
First-time user sees: project → scan → findings. Advanced features discoverable.
Dismiss, override, reclassify, golden source — not a dead end.
Information density prioritized. Whitespace is functional.
Creates value between Figma, Storybook, and GitHub — does not replace them.
Scope
Problem research
Personas
Competitive analysis
Information architecture
User flows
Growth model
Interactive prototype